AI Engineer

Digital Waffle; Greater London; On-site; GBP 90,000 - 110,000; Full time

Benefits offered by this job

Competitive salary

Flexible working

Professional growth opportunities

Leadership path

Job summary

Digital Waffle is seeking an AI Solutions Architect to design and build our in-house AI environment in London and lead the initial AI engineering team. You will own the infrastructure strategy, establish MLOps practices, and collaborate with product and data teams to enable rapid model development and deployment.

This is a senior, hands-on leadership role with a path to grow the team. You will recruit and mentor two mid-level AI engineers, set up scalable compute, and implement robust CI/CD and

Qualifications

• 5+ years of experience in machine learning, data science, or AI system design.
• Proven track record of deploying ML models or LLM-based applications to production.
• Strong programming fundamentals, including data structures and algorithms.
• Hands-on experience with transformers, embeddings, and vector databases.
• Experience running AI workloads on offline or on-premise platforms (non-cloud environments).
• Solid understanding of data pipelines, APIs, and scalable system architecture.

Responsibilities

• Architect, build, and maintain an in-house AI environment (on-prem or hybrid cloud).
• Design MLOps workflows for training, deploying, and monitoring models.
• Integrate and manage containerized AI engines (Docker/Kubernetes).
• Establish best practices for model versioning, data pipelines, and reproducibility.
• Collaborate with ML and NLP researchers to optimize infrastructure for experimentation.
• Set up CI/CD pipelines, monitoring tools, and scalable compute infrastructure.
• Lead future recruitment and mentoring of additional AI engineers.

Skills

5+ years ML/AI system design

Production ML deployments

Data structures & algorithms

Transformers embeddings vector DB

On-prem/offline AI workloads

Data pipelines & APIs

Tools

Docker

Kubernetes

CI/CD

Job description

AI Solutions Architect - Build Our In-House AI Environment

Location: London (onsite)

Type: Full-time | Permanent

Salary: Up to £110k total compensation

About Us

We're an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker - but it's time to take the next step. We're ready to build our own in-house AI environment, giving us full control over our models, data, and innovation pipeline.

To make that happen, we're looking for an AI Infrastructure Lead - someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business.

The Role

As our first senior AI hire, you'll take ownership of designing and building the foundation of our AI ecosystem. You'll shape the infrastructure strategy, establish our MLOps pipelines, and work closely with product and data teams to enable seamless model development and deployment. Once the environment is established, you'll play a key role in recruiting and mentoring two mid-level AI engineers who will join your team.

Responsibilities

• Architect, build, and maintain an in-house AI environment (on-prem or hybrid cloud).
• Design MLOps workflows for training, deploying, and monitoring models.
• Integrate and manage containerized AI engines (Docker/Kubernetes).
• Establish best practices for model versioning, data pipelines, and reproducibility.
• Collaborate with ML and NLP researchers to optimize infrastructure for experimentation.
• Set up CI/CD pipelines, monitoring tools, and scalable compute infrastructure.
• Lead future recruitment and mentoring of additional AI engineers.

Skills & experience

Required

• 5+ years of experience in machine learning, data science, or AI system design.
• Proven track record of deploying ML models or LLM-based applications to production.
• Strong programming fundamentals, including data structures and algorithms.
• Hands-on experience with transformers, embeddings, and vector databases.
• Experience running AI workloads on offline or on-premise platforms (non-cloud environments).
• Solid understanding of data pipelines, APIs, and scalable system architecture.

Preferred

• Experience leading small teams or mentoring other engineers.
• Familiarity with MLOps tools and best practices.
• Background in integrating AI solutions into enterprise products.
• Awareness of privacy, bias mitigation, and model explainability techniques.

What We Offer

• Opportunity to design and own the company's AI infrastructure from the ground up.
• Work with cutting-edge AI technologies in a hands-on, high-impact role.
• Leadership path - build your own AI engineering team.
• Competitive salary (up to £110k), flexible working, and professional growth opportunities.

Ready to build the foundation of our AI future?